Sayed-Amir Marashi

Associate Professor at University of Tehran (@UnivOfTehran); interested in #Bioinformatics, #SystemsBiology and #MetabolicEngineering

[Sayed-Amir Marashi @_marashi_]

👋Long time no see!
I'm back! From now on, I'll be focusing on sharing scientific publications – either my own or the ones that pique my interest.
(🇮🇷Well, if you're familiar with my views, you know where I stand on politics & other hot topics🇵🇸. If not, no worries!🌍🌏🌎)

[Prof. Nikolai Slavov @slavov_n]

An intuitive visualization of the regulatory layers influencing the stoichiometry of a protein complex.

https://t.co/J6oP8grfzJ

[Microbiome @MicrobiomeJ]

In #Microbiome

🚀Exploring how NASA's mission spacecraft assembly cleanrooms host 26 novel bacterial species

🦠These microbes form biofilms, resist various stressors & hold biotechnological potential

🚨https://t.co/Po9qKqcuUJ

[Sam Rodriques @SGRodriques]

Read the paper here: https://t.co/M7HNV1THnZ

and our blog post: https://t.co/gaRH0KingW

[Sayed-Amir Marashi @_marashi_]

Postmortem catabolism!
https://t.co/VpkdlaNEFH

[Sayed-Amir Marashi @_marashi_]

https://t.co/tyVhpa5aZT

[good papers @paperperday]

Biocomputing at the crossroad between emulating artificial intelligence and cellular supremacy
https://t.co/0IXNpvY2dP

[owl @owl_posting]

today, an enzyme design paper from the Baker lab came out

its very, very hard to read

luckily, you dont need to! bc @eryney_ok and i toiled for hours to walk through it in @AsimovPress: explaining what enzyme they redesigned, how they did it, and the validation involved

[Krell Laboratory @KrellLaboratory]

Very pleased to see that out in PNAS: Bacterial sensor evolved by decreasing complexity. Evolution is not always towards complexity. Yet another wonderful collaboration with @zhulinlab @gavirius and @miguel_matilla,@BLASTMeetings @SEMicrobiologia https://t.co/Qp3woqCrFZ

[Tae Hoon Kim @taehoonkim]

A synthetic protein-level neural network in mammalian cells | Science https://t.co/PZTIl6TT55

[Jerzy Szablowski @JerzySzablowski]

qPCR can measure expression of virtually any gene... in homogenized tissues. Here, we show an "in-vivo qPCR" equivalent, where we measure a sequence-specific transcript with synthetic serum markers and enzyme-based signal amplification.
https://t.co/pUisE5gesh

[Hani Goodarzi @genophoria]

@iamjohnnyyu, @nalidoust, @kevansf, and I are excited to announce a historic achievement by our team at @vevo_ai: Tahoe-100M, a 100M single-cell transcriptomic atlas, measuring how thousands of drugs impact cells from 50 diverse cancer lines.
https://t.co/XT6wGV10aA

[Sayed-Amir Marashi @_marashi_]

Wow! 😳
https://t.co/BOZxswygz5

[Olivier Borkowski @O_Borkowski]

Open-ended molecular recording of sequential cellular events into DNA
https://t.co/wnryqCSxms

[Niko McCarty. @NikoMcCarty]

Biotechnologists are increasingly working to engineer microbes and then release them into the "real-world" to clean up pollution, etc.

A major demonstration of this was published yesterday, in a study showing that bacteria can be engineered to detect TNT explosives in soil.

***

It's called "An autonomous microbial sensor enables long-term detection of TNT explosive in natural soil." This work was done as part of a DARPA program to build engineered organisms for real-world capabilities. There are some obvious military applications here.

The study's authors engineered Bacillus subtilis microbes to detect TNT contamination in soil, showing they maintained functionality over a 28-day period.

The circuit works like this: First, the authors made a RIBOSWITCH (an RNA molecule that folds up and precisely binds to a target molecule; in this case TNT) using an online tool called the "Riboswitch Calculator." (Available here: https://t.co/zLEXhvMJzK) When this riboswitch grabs onto tRNA, its 3D shape changes, thus revealing a sequence encoding an INTEGRASE enzyme. Integrase enzymes grab onto specific DNA "codes" and then flip them around 180 degrees. They basically just switch the orientation of a DNA sequence.

Second, this integrase enzyme gets expressed within the cells. It grabs onto a DNA sequence (like a key fitting into a lock), and flips them around. The authors used the integrase enzyme to flip around the orientation of a PROMOTER sequence that controls gene expression.

And finally, once the promoter gets flipped around, a "response" module switches on. This response module can be anything; it could be a gene encoding green fluorescent protein, a pigment, or a gaseous molecule. It simply produces a detectable output, thus linking the presence of TNT to some kind of visual or odorous output.

When mixed with a small amount of TNT (4.5 mg TNT per kg) in soil, the B. subtilis cells had a 14-fold activation in their response output after one week. The cells maintained stable activation for over 21 days. The response does decay away after awhile, though; it has a half-life of about 5 days.

Now an obvious question is: Once you put these engineered microbes into the soil, how do you get them out again?

Well, you don't. But there is some good news in the paper: the engineered microbes compete with bacteria that naturally grow in the soil, and the population of engineered cells therefore diminish over time. After a month or more, the engineered bacteria were down to 1% of their initial population size.

Many similar studies are soon to come...

Full paper here: https://t.co/OzYPvTSLkf

[Sayed-Amir Marashi @_marashi_]

Wow!
https://t.co/Qgl3tezQzo

[Sayed-Amir Marashi @_marashi_]

Nucleotide Transformers!
https://t.co/WPP1KdgNqM

[Niko McCarty. @NikoMcCarty]

Playing Pac-Man with Living Cells 🦠

Euglena (a type of algae that responds to light) cells were placed in a microfluidic maze, which acts like a game board.

Players move the cell around using LED lights, situated on each edge of the board. The cells move away from light stimulation (after a time delay of about 1 second; very laggy!)

A computer vision system tracks the cell's position and overlays virtual ghosts + fruits to complete the Pac-Man game. This is one of my favorite papers, just because it ties together biology and computer science concepts in a creative way.

[James Zou @james_y_zou]

Protein language models (PLM) are goldmines; now we know what they learn.

📢Thrilled to share #interPLM: interpreting how >2500 bio concepts are captured by PLM via SAEs.

We also found many NEW concepts in PLM and use #LLM to explain what they are to fill in gaps in databases🧵

[Seth Bordenstein @Symbionticism]

Article: https://t.co/HzgzGj3lt4

[Sayed-Amir Marashi @_marashi_]

https://t.co/GWKbmrGHui

[Science Magazine @ScienceMagazine]

This light-sheet microscopy three-dimensional rendering shows a first-of-its-kind mouse whole-brain mRNA analysis at single-cell resolution.

Learn more in this week’s issue: https://t.co/TC95lPspFC

[Kaiyi Jiang @idmjky]

Thrilled to share that EVOLVEpro is now published @ScienceMagazine Since our preprint, we now demonstrate low-N eningeering of both antibody and enzymes. We hope this model will broadly useful to the protein engineering field. https://t.co/vMzLFNkcnD